OpenAI Machine Learning Engineer Interview Questions + Guide in 2024
Overview
OpenAI is a pioneering AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity, pushing the boundaries of AI capabilities, and seeking to safely deploy them through products like ChatGPT and the OpenAI API.
The Machine Learning Engineer position involves working on retrieval and search problems across API and ChatGPT. As this technology evolves, retrieval and search have become crucial use cases, and this role will place you at the center of these efforts, impacting millions of users. Candidates will collaborate on search algorithms, deploy these solutions in production, and explore novel research topics. Strong experience building and maintaining production ML systems, especially for search and retrieval, is essential.
In this guide, we will help you navigate the interview process for this exciting role, including important steps and typical OpenAI machine learning engineer interview questions you might encounter. Let’s get started!
What is the Interview Process Like for a Machine Learning Engineer Role at OpenAI?
The interview process usually depends on the role and seniority; however, you can expect the following on an OpenAI machine learning engineer interview:
Recruiter/Hiring Manager Call Screening
If your CV is among the shortlisted few, a recruiter from the OpenAI Talent Acquisition Team will contact you and verify key details like your experiences and skill level. Behavioral questions may also be part of the screening process.
Sometimes, the OpenAI hiring manager will stay present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.
The whole recruiter call should take about 30 minutes.
Technical Virtual Interview
Successfully navigating the recruiter round will invite you to the technical screening round. The technical screening for the OpenAI Machine Learning Engineer role is usually conducted virtually, including through video conference and screen sharing. Questions in this 1-hour interview stage may revolve around OpenAI’s data systems, ETL pipelines, and SQL queries.
Your proficiency against hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed during the round.
Case studies and similar real-scenario problems may also be assigned depending on the position’s seniority.
Coding Interview Rounds
You typically go through three to four intensive coding interview rounds for this stage daily. These sessions usually comprise:
- Two ML-focused interviews
- One CS (Computer Science)-focused interview
- A session with a recruiter discussing your interests and fit for the role
Research Presentation (If applicable)
If you are interviewing for a research-centric position, a presentation on your past research might be required. This presentation helps assess your knowledge depth and ability to convey complex concepts clearly.
Onsite Interview Rounds
Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds will be conducted during your day at the OpenAI office, varying with the role. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the finalized candidates throughout these interviews.
If you were assigned take-home exercises, you may also be invited to a presentation round during the on-site interview for the Machine Learning Engineer role at OpenAI.
What Questions Are Asked in an OpenAI Machine Learning Engineer Interview?
Typically, interviews at OpenAI vary by role and team, but commonly, Machine Learning Engineer interviews follow a fairly standardized process across these question topics.
1. How would you measure the effectiveness of extra pay for delivery drivers during peak hours?
If you work at a food delivery company, how would you measure the effectiveness of giving extra pay to delivery drivers during peak hours to meet consumer demand?
2. Write a function rain_days to calculate the probability of rain on the nth day after today.
It will likely rain tomorrow, depending on whether it rained today or yesterday. If it rained both days, there’s a 20% chance of rain tomorrow. If it rained one of the days, there’s a 60% chance. If it rained neither day, there’s a 20% chance. Given that it rained today and yesterday, calculate the probability it will rain the day after today.
3. What are the assumptions of linear regression?
List and explain the key assumptions that must be met for linear regression analysis to be valid.
How to Prepare for a Machine Learning Engineer Interview at OpenAI
To help you succeed in your OpenAI machine learning engineer interviews, consider these tips based on interview experiences:
Brush Up on Technical Skills: Plan to brush up on technical skills and try as many practice interview questions and mock interviews as possible on Interview Query.
Understand OpenAI’s Mission: OpenAI deeply values its mission to ensure AI benefits all of humanity. Be prepared to discuss your views on AI safety and ethical considerations.
Collaboration and Adaptability: OpenAI operates in a fast-paced, sometimes loosely defined environment. It will be crucial to demonstrate your ability to collaborate effectively and adapt to changing priorities.
FAQs
What is the average salary for a Machine Learning Engineer at OpenAI?
According to Glassdoor, machine learning engineers at OpenAI earn between $104K to $146K per year, with an average of $123K per year.
What does the Machine Learning Engineer role at OpenAI entail?
In this role, you will work on retrieval and search algorithms, collaborate closely with the research team, deploy methodologies into production, and explore novel research topics. You’ll also partner with engineers, product managers, and designers to bring new features.
What skills are required for the Machine Learning Engineer role at OpenAI?
You should have extensive experience building and maintaining production machine learning systems, familiarity with vector databases or search indices, and expertise in building internet-scale search systems. The ability to own problems end-to-end and move quickly in a dynamic environment is also essential.
What is OpenAI’s mission and work culture?
OpenAI is dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. The company values safety over unfettered growth and focuses on creating an inclusive culture where diverse perspectives are welcomed. OpenAI encourages radical candor and the challenging of groupthink.
The Bottom Line
If you want more insights about the company, check out our main OpenAI Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about OpenAI’s interview process for different positions.
You can also check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.
Good luck with your interview!